# compute

From neuralnet v1.33
by Frauke Guenther

##### Computation of a given neural network for given covariate vectors

`compute`

, a method for objects of class `nn`

, typically
produced by `neuralnet`

.
Computes the outputs of all neurons for specific arbitrary covariate vectors given a trained neural network. Please make sure that the order of the covariates is the same in the new matrix or dataframe as in the original neural network.

- Keywords
- neural

##### Usage

`compute(x, covariate, rep = 1)`

##### Arguments

- x
- an object of class
`nn`

. - covariate
- a dataframe or matrix containing the variables that had been used to train the neural network.
- rep
- an integer indicating the neural network's repetition which should be used.

##### Value

`compute`

returns a list containing the following components:##### Examples

```
Var1 <- runif(50, 0, 100)
sqrt.data <- data.frame(Var1, Sqrt=sqrt(Var1))
print(net.sqrt <- neuralnet(Sqrt~Var1, sqrt.data, hidden=10,
threshold=0.01))
compute(net.sqrt, (1:10)^2)$net.result
```

*Documentation reproduced from package neuralnet, version 1.33, License: GPL (>= 2)*

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